Australian e-Health Research Centre, CSIRO, UQ Health Sciences Building 901/16, Royal Brisbane and Women's Hospital, Herston, 4029, Australia.
Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute, 1G Royal Parade, Parkville, 3052, Australia; Department of Paediatrics, University of Melbourne, Flemington Road, Parkville, 3052, Australia.
Patient Educ Couns. 2021 Apr;104(4):739-749. doi: 10.1016/j.pec.2020.11.007. Epub 2020 Nov 10.
To support informed decision-making about reanalysis of clinical genomic data for risk of preventable conditions ('additional findings') by developing a chatbot (electronic genetic resource, 'eDNA').
Interactions in pre-test genetic counseling sessions (13.5 h) about additional findings were characterized using proponent, thematic and semantic analyses of transcripts. We then wrote interfaces to draw supplementary data from external genetics applications. To create Edna, this content was programmed using a chatbot framework which interacts with patients via speech-to-text.
Conditions, terms, explanations of concepts, and key factors to consider in decision making were all encoded into chatbot conversations emulating counseling session flows. Patient agency can be enhanced by prompted consideration of the personal and familial implications of testing. Similarly, health literacy can be broadened through explanation of genetic conditions and terminology. Novel aspects include sentiment analysis and collection of family history. Medical advice and the impact of existing genetic conditions were deemed inappropriate for inclusion.
Edna's successful development represents a movement towards accessible, acceptable and well-supported digital health processes for patients to make informed decisions for additional findings.
Edna complements genetic counseling by collecting and providing genomic information before or after pre-test consultations.
通过开发一个聊天机器人（电子遗传资源，“eDNA”）来支持对临床基因组数据进行重新分析以预防可预防疾病（“附加发现”）的决策。
通过对转录本进行支持者、主题和语义分析，对附加发现的预测试遗传咨询会议（13.5 小时）中的交互进行了描述。然后，我们编写了接口来从外部遗传应用程序中提取补充数据。为了创建 Edna，我们使用聊天机器人框架通过语音转文本与患者进行交互来编程此内容。
将条件、术语、概念解释以及决策中需要考虑的关键因素都编码到了模仿咨询会议流程的聊天机器人对话中。通过提示患者考虑测试对个人和家庭的影响，可以增强患者的代理能力。同样，通过解释遗传条件和术语，可以拓宽健康素养。新颖的方面包括情感分析和家族史收集。医学建议和现有遗传状况的影响被认为不适合包含在内。
Edna 的成功开发代表了一种可访问、可接受和有充分支持的数字健康流程，使患者能够为附加发现做出明智的决策。
Edna 通过在预测试咨询之前或之后收集和提供基因组信息来补充遗传咨询。
